Instructions to use Vinz9899/dumy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vinz9899/dumy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Vinz9899/dumy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Vinz9899/dumy-model") model = AutoModelForSequenceClassification.from_pretrained("Vinz9899/dumy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e74e5e5b77ab197625e4b37bb7c0b0b8e906a2abefdb2f336b1cd0d15c8dca18
- Size of remote file:
- 438 MB
- SHA256:
- dbe9ed6180d1cacf1b106bbc7e5170473fde3be0520946047fd5f3e4bc6b24a8
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